2017/02/03 by Brunella Spinelli, Spinelli, Brunella, L. Elisa Celis +3
Computer Science · Medicine · Physics and Astronomy · #Complex Network Analysis Techniques #Data-Driven Disease Surveillance #FOS: Computer and information sciences #SARS-CoV-2 detection and testing #Social and Information Networks (cs.SI) #cs.SI
paper · pdf · doi:10.48550/arxiv.1702.01056
Accepted for presentation at WWW '17
openalex publication_date 2017/02/03 · arxiv created 2017/02/06 · arxiv updated 2017/02/07 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Source localization, the act of finding the originator of a disease or rumor in a network, has become an important problem in sociology and epidemiology. The localization is done using the infection state and time of infection of a few designated sensor nodes; however, maintaining sensors can be very costly in practice. We propose the first online approach to source localization: We deploy a priori only a small number of sensors (which reveal if they are reached by an infection) and then iteratively choose the best location to place new sensors in order to localize the source. This approach allows for source localization with a very small number of sensors; moreover, the source can be found while the epidemic is still ongoing. Our method applies to a general network topology and performs well even with random transmission delays.